International Business Machines Corporation
Automatically identifying and minimizing potentially indirect meanings in electronic communications

Last updated:

Abstract:

A computer system evaluating an input segment of a communication, in parallel, by a baseline classification model trained with baseline passages indicating dictionary meaning and multiple generative sequence models each trained to classify a particular passage from among multiple indirect passages indicating usage with an indirect meaning, to receive a separate score from the baseline classification model and each of the generative sequence models, each separate score indicating a classification probability for the input segment. The computer system, responsive to one or more particular scores generated by one or more of the generative sequence models exceeding a baseline score generated by the baseline classification model summed with a tuning factor, flagging the input segment as having a potentially indirect meaning.

Status:
Grant
Type:

Utility

Filling date:

12 Jul 2019

Issue date:

2 Nov 2021